Geosciences data mining

<p>Our world consists of different areas which contain a massive amount of data and interact with each other. Scientists apply computer-oriented operations of detecting patterns in voluminous assemblies of data comprehending techniques at the intercrossing of artificial intelligence, machine learning, statistics, &nbsp;&nbsp; mathematic and database systems. Basically, the overall &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; problem is to pick out information from databases and transfashion it up to user-friendly organization.&nbsp; The geographic study outburst is not quite different from resembling revolutions in marketing, biology, and astronomy. Today the problems associated with the study of the geographic environment attract a strong interest in modern Data Analysis and Computer Science. Recently, newly developed methods of data processing and analysis are focused on the active participation of experts of the data domain.</p><p>&nbsp;</p><p>&nbsp;Therefore, the principal goal of this paper is to group data of the marine environment. With the help of the new method of the cluster analysis &quot;Carticlus&quot;, I will reveal sea areas with similar trends (parameters) and draw an analogy between obtained information and reality.</p><p>&nbsp;</p><p>For our study purposes we use State Research Center &quot;Arctic and Antarctic Reserch Institute&quot; database of the Barents Sea parameters observations, which was composed of seven main parameters:</p><ul><li>temperature</li><li>total salt content</li><li>latitude</li><li>longitude</li></ul><p>As a result I have realization of Carticlus algorithm and results of clasterization of our data.</p>